The above GSE ID given GSE47910 has agilent microarray raw data in .txt file for every sample (ie, 498 samples here) As the blow code works on affymetrix arrays-
> data = ReadAffy(celfile.path=celpath)
> data.rma = rma(data)
> data.matrix = exprs(data.rma)
> write.table(data.matrix, file='/mnt/store_room/Dataset1/processing/validation/newRMAGSE65663.txt')
I need a similar RMA normalization code for agilent microarrays. if not RMA, then any other normalization method that gives out a matrix with all samples in columns and probes_IDs in rows with normalised values given. I am new to microarray analysis. please help
1 answer
We don't use RMA for Agilent arrays. We can still normalise via quantile, or LOESS, though. The background correction step is also different, usually via normexp.
For Agilent single-colour arrays, I posted some code here: How to process (seems) Agilent microarrry data?
For two-colour arrays, I posted code here: build the expression matrix step by step from GEO raw data
Further, there is information in the limma user's guide[1] about how to process these arrays.
Note Bene - both of my posts are guided by the limma user's guide[1].
Kevin
Ref:
- Smyth GK, Ritchie M, Thorne N, Wettenhall J, Shi W, Hu Y, limma: Linear Models for Microarray and RNA-Seq Data User’s Guide, https://www.bioconductor.org/packages/devel/bioc/vignettes/limma/inst/doc/usersguide.pdf
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